This function spCovAdd allows to build optimization scenarios based on spatial coverage method.
spCovAdd( observations, candidates, nDiff, nGridCells, plotOptim = TRUE, nTry, ... )data.frame of optimized locations
object of class data.frame with x,y coordinates
a SpatialPolygonsDataFrame to explore: in use when optimizing
the implementation of new measurement stations to an existing network
number of stations to add or delete
number of grid cells to work on spatial coverage strafication
logical; to plot the result or not
the method will try nTry initial configurations and will keep
the best solution in order to reduce the risk of ending up with an unfavorable solution
other arguments to be passed on at lower level functions such as
stratify
Olivier Baume
This function allows to build optimization scenarios based on spatial coverage method.
The scenario action is "add". To add new measurement locations to the running network,
the function uses function stratify from package spcosa.
Function stratify adds new strata to the domain study.
D. J. Brus, J. de Gruijter, J. van Groenigen (2006). Designing spatial coverage samples using the k-means clustering algorithm. In A. McBratney M. Voltz and P. Lagacherie, editor, Digital Soil Mapping: An Introductory Perspective, Developments in Soil Science, vol. 3., Elsevier, Amsterdam.